Chitin Nanofibers Enable the Colloidal Dispersion of Carbon Nanomaterials in Aqueous Phase and Hybrid Material Coassembly.

Chitin nanofibrils (ChNF) sourced from discarded marine biomass are shown as effective stabilizers of carbon nanomaterials in aqueous media. Such stabilization is evaluated for carbon nanotubes (CNT) considering spatial and temporal perspectives by using experimental (small-angle X-ray scattering, among others) and theoretical (atomistic simulation) approaches. We reveal that the coassembly of ChNF and CNT is governed by hydrophobic interactions, while electrostatic repulsion drives the colloidal stabilization of the hybrid ChNF/CNT system. Related effects are found to be transferable to multiwalled carbon nanotubes and graphene nanosheets. The observations explain the functionality of hybrid membranes obtained by aqueous phase processing, which benefit from an excellent areal mass distribution (correlated to piezoresistivity), also contributing to high electromechanical performance. The water resistance and flexibility of the ChNF/CNT membranes (along with its tensile strength at break of 190 MPa, conductivity of up to 426 S/cm, and piezoresistivity and light absorption properties) are conveniently combined in a device demonstration, a sunlight water evaporator. The latter is shown to present a high evaporation rate (as high as 1.425 kg water m-2 h-1 under one sun illumination) and recyclability.

Hybrid Filtering Compensation Algorithm for Suppressing Random Errors in MEMS Arrays.

To solve the high error phenomenon of microelectromechanical systems (MEMS) due to their poor signal-to-noise ratio, this paper proposes an online compensation algorithm wavelet threshold back-propagation neural network (WT-BPNN), based on a neural network and designed to effectively suppress the random error of MEMS arrays. The algorithm denoises MEMS and compensates for the error using a back propagation neural network (BPNN). To verify the feasibility of the proposed algorithm, we deployed it in a ZYNQ-based MEMS array hardware. The experimental results showed that the zero-bias instability, angular random wander, and angular velocity random wander of the gyroscope were improved by about 12 dB, 10 dB, and 7 dB, respectively, compared with the original device in static scenarios, and the dispersion of the output data was reduced by about 8 dB in various dynamic environments, which effectively verified the robustness and feasibility of the algorithm.

Monodispersed Renewable Particles by Cascade and Density Gradient Size Fractionation to Advance Lignin Nanotechnologies.

Control over particle size and shape heterogeneity is highly relevant to the design of photonic coatings and supracolloidal assemblies. Most developments in the area have relied on mineral and petroleum-derived polymers that achieve well-defined chemical and dimensional characteristics. Unfortunately, it is challenging to attain such control when considering renewable nanoparticles. Herein, a pathway toward selectable biobased particle size and physicochemical profiles is proposed. Specifically, lignin is fractionated, a widely available heterogeneous polymer that can be dissolved in aqueous solution, to obtain a variety of monodispersed particle fractions. A two-stage cascade and density gradient centrifugation that relieves the need for solvent pre-extraction or other pretreatments but achieves particle bins of uniform size (~60 to 860 nm and polydispersity, PDI<0.06, dynamic light scattering) along with characteristic surface chemical features is introduced. It is found that the properties and associated colloidal behavior of the particles are suitably classified in distinctive size populations, namely, i) nanoscale (50-100 nm), ii) photonic (100-300 nm) and iii) near-micron (300-1000 nm). The strong correlation that exists between size and physicochemical characteristics (molar mass, surface charge, bonding and functional groups, among others) is introduced as a powerful pathway to identify nanotechnological uses that benefit from the functionality and cost-effectiveness of biogenic particles.

Associations Between Beverage Consumption and Risk of Microvascular Complications Among Individuals With Type 2 Diabetes.

CONTEXT: The relationship between the consumption of different beverages and the risk of microvascular complications in individuals with type 2 diabetes (T2D) is unclear. OBJECTIVE: To investigate the association of individual beverage consumption, including artificially sweetened beverages (ASBs), sugar-sweetened beverages (SSBs), tea, coffee, natural juice, and yogurt, with the risk of microvascular complications in adults with T2D. METHODS: This cohort study included 6676 participants with T2D who were free of macrovascular and microvascular complications at baseline in the UK Biobank. Cox proportional hazard models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: During a median follow-up of 11.7 years, 1116 cases of composite microvascular complications were documented. After multivariable adjustment, a linear dose-response relationship was demonstrated between the consumption of ASBs and SSBs and the risk of microvascular complications. Compared with nonconsumers, those who consumed ≥2.0 units/day of ASBs and SSBs had an HR (95% CI) of 1.44 (1.18-1.75) and 1.32 (1.00-1.76) for composite microvascular complications, respectively. In addition, higher tea consumption was associated with a lower risk of diabetic retinopathy, with an HR (95% CI) of 0.72 (0.57-0.92) for whom consuming ≥4.0 units/day. There was no significant association between individual beverage consumption and the risk of diabetic neuropathy. No significant association was observed between the consumption of coffee, natural juice, or yogurt and the risks of microvascular complications. Moreover, substituting half units/day of ASBs or SSBs with tea or coffee was associated with a 16% to 28% lower risk of microvascular complications. CONCLUSION: Higher consumption of ASBs and SSBs was linearly associated with an increased risk of microvascular complications in adults with T2D.

Pattern recognition of microcirculation with super-resolution ultrasound imaging provides markers for early tumor response to anti-angiogenic therapy.

Rationale: Cancer treatment outcome is traditionally evaluated by tumor volume change in clinics, while tumor microvascular heterogeneity reflecting tumor response has not been fully explored due to technical limitations. Methods: We introduce a new paradigm in super-resolution ultrasound imaging, termed pattern recognition of microcirculation (PARM), which identifies both hemodynamic and morphological patterns of tumor microcirculation hidden in spatio-temporal space trajectories of microbubbles. Results: PARM demonstrates the ability to distinguish different local blood flow velocities separated by a distance of 24 µm. Compared with traditional vascular parameters, PARM-derived heterogeneity parameters prove to be more sensitive to microvascular changes following anti-angiogenic therapy. Particularly, PARM-identified "sentinel" microvasculature, exhibiting evident structural changes as early as 24 hours after treatment initiation, correlates significantly with subsequent tumor volume changes (|r| > 0.9, P < 0.05). This provides prognostic insight into tumor response much earlier than clinical criteria. Conclusions: The ability of PARM to noninvasively quantify tumor vascular heterogeneity at the microvascular level may shed new light on early-stage assessment of cancer therapy.

Voluntary blood donation preferences in China: A discrete choice experiment among experienced and inexperienced donors.

BACKGROUND AND OBJECTIVES: Due partly to an ageing population, China faces an increasingly dire blood shortage crisis requiring greater voluntary blood donations. A better understanding of blood donation preferences can inform blood donation policies and potentially increase donations. We used an online survey and discrete choice experiment to achieve our study objective: identify the most influential structural facilitators and barriers to voluntary blood donation in China. MATERIALS AND METHODS: First, we identified six structural attributes (travel time, venue, donation volume, paid leave, scheduling and gifts) that were hypothesized to influence voluntary blood donation; attribute selection was based on a literature review and qualitative interviews. Second, a d-efficient design with 36 choice sets and 9 blocks was developed. Participants were asked to complete four choice sets, and in each choice set, they were asked to choose from three options: two voluntary blood donation scenarios and a 'Do not donate blood' option. Study participants were recruited through an online survey platform company in China. Voluntary blood donation preferences and preferences by blood donation history were estimated with random-parameter logit models and interaction terms. RESULTS: In 2022, 1185 individuals enrolled in the study. Most participants had college education (92%). Generally, participants preferred longer paid leave, lower blood donation volumes and gifts after donation. Based on interaction analyses, experienced and inexperienced donors exhibited similar preferences. CONCLUSION: Campaigns to increase voluntary blood donation rates in China should consider implementing paid leave after voluntary blood donation, lower blood donation volumes and small gifts conferred after donation.

The efficacy and safety of enhanced recovery after surgery (ERAS) Program in laparoscopic distal gastrectomy: a systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: Although ERAS Program had some advantages in laparoscopic distal gastrectomy (LDG), its efficacy and safety remained unclear. We conducted a systematic review and meta-analysis to assess the efficacy and safety of the ERAS group and the traditional care (TC) group in LDG. METHODS: Multiple databases were retrieved from 1 January 2000 to 30 April 2023. The risk ratio (RR), standardized mean difference (SMD) and their 95% confidence interval (CI) were used to estimate the results. RESULTS: Our meta-analysis contained 17 randomized controlled trials (RCTs) studies, which comprised 1468 patients. Regarding efficacy, the ERAS group had significantly shorter postoperative time to first flatus (SMD = -1.29 [95% CI: -1.68, -0.90]), shorter time to first defecation (SMD = -1.26 [95% CI: -1.90, -0.61]), shorter hospital stays (SMD = -0.99 [95% CI: -1.34, -0.63]), and lower hospitalization costs (SMD = -1.17 [95% CI: -1.86, -0.48]) compared to the TC group. Furthermore, in the ERAS group, C-reactive protein levels were lower on postoperative days 1, 3 or 4, and 7; albumin levels were higher on postoperative days 3 or 4 and 7; and interleukin-6 levels were lower on postoperative days 1 and 3. Regarding safety, the overall postoperative complication rate was lower in the ERAS group (RR: 0.76 [95% CI: 0.60, 0.97]), but there was no significant difference in the individual postoperative complication rate. Other indicators were also not statistically significant. CONCLUSION: The combination of ERAS Program with laparoscopy surgery was safe and effective for the perioperative management of patients with distal gastric cancer.

Vibration Analysis and Damping Effect of Blade-Hard Coating Composite Structure Based on Base Excitation.

Hard coatings are widely employed on blades to enhance impact resistance and mitigate fatigue failure caused by vibration. While previous studies have focused on the dynamic characteristics of beams and plates, research on real blades remains limited. Specifically, there is a lack of investigation into the dynamic characteristics of hard-coated blades under base excitation. In this paper, the finite element model (FEM) of blade-hard coating (BHC) composite structure is established based on finite element methods in which the hard coating (HC) material and the substrate are considered as the isotropic material. Harmonic response analysis is conducted to calculate the resonance amplitude of the composite under base excitation. Numerical simulations and experimental tests are performed to examine the effects of various HC parameters, including energy storage modulus, loss factors, coating thickness, and coating positions, on the dynamic characteristics and vibration reduction of the hard-coated blade composite structures. The results indicate that the difference in natural frequency and modal loss factor of blades increases with higher storage modulus and HC thickness. Moreover, the vibration response of the BHC decreases with higher storage modulus, loss factor, and coating thickness of the HC material. Blades with a complete coating exhibit superior damping effects compared to other coating distributions. These findings are significant for establishing accurate dynamic models of HC composite structures, assessing the effectiveness of HC vibration suppression, and guiding the selection and preparation of HC materials.

A novel nomogram for predicting microvascular invasion in hepatocellular carcinoma.

INTRODUCTION AND OBJECTIVES: In hepatocellular carcinoma (HCC), the prognosis of patients with microvascular invasion (MVI) is poor. Therefore, in this study, we established and evaluated the performance of a novel nomogram to predict MVI in patients with HCC. MATERIALS AND METHODS: We retrospectively obtained clinical data of 497 patients with HCC who underwent hepatectomy at Liaoning Cancer Hospital from November 1, 2018, to November 4, 2021. The patients (n = 497) were randomized in a 7:3 ratio into the training cohort (TC, n = 349) and the validation cohort (VC, n = 148). We performed Least Absolute Shrinkage and Selection Operator (LASSO) and univariate as well as multivariate logistic regression analyses (ULRA, MRLA) on patients in the TC to identify factors independently predicting MVI. RESULTS: Preoperative FIB-4, AFU, AFP levels, liver cirrhosis, and non-smooth tumor margin were independent risk factors for preoperative MVI prediction. The C-index of the TC, VC, and the entire cohort was 0.846, 0.786, and 0.829, respectively. The calibration curves demonstrated the outstanding agreement between predicted MVI incidences by our model and the actual MVI risk. Decision curve analysis (DCA) confirmed the significance of our predictive model in clinical settings. The Kaplan-Meier (KM) survival curve showed that the recurrence-free survival (RFS) and overall survival (OS) of patients in the high-MVI risk group were poor compared to those in the low-MVI risk group. CONCLUSIONS: We constructed and evaluated the performance of the novel nomogram for predicting MVI risk. Our predictive model could adequately predict MVI risk and aid clinicians in selecting appropriate therapeutic strategies for patients.

Monoallelic variation in DHX9, the gene encoding the DExH-box helicase DHX9, underlies neurodevelopment disorders and Charcot-Marie-Tooth disease.

DExD/H-box RNA helicases (DDX/DHX) are encoded by a large paralogous gene family; in a subset of these human helicase genes, pathogenic variation causes neurodevelopmental disorder (NDD) traits and cancer. DHX9 encodes a BRCA1-interacting nuclear helicase regulating transcription, R-loops, and homologous recombination and exhibits the highest mutational constraint of all DDX/DHX paralogs but remains unassociated with disease traits in OMIM. Using exome sequencing and family-based rare-variant analyses, we identified 20 individuals with de novo, ultra-rare, heterozygous missense or loss-of-function (LoF) DHX9 variant alleles. Phenotypes ranged from NDDs to the distal symmetric polyneuropathy axonal Charcot-Marie-Tooth disease (CMT2). Quantitative Human Phenotype Ontology (HPO) analysis demonstrated genotype-phenotype correlations with LoF variants causing mild NDD phenotypes and nuclear localization signal (NLS) missense variants causing severe NDD. We investigated DHX9 variant-associated cellular phenotypes in human cell lines. Whereas wild-type DHX9 was restricted to the nucleus, NLS missense variants abnormally accumulated in the cytoplasm. Fibroblasts from an individual with an NLS variant also showed abnormal cytoplasmic DHX9 accumulation. CMT2-associated missense variants caused aberrant nucleolar DHX9 accumulation, a phenomenon previously associated with cellular stress. Two NDD-associated variants, p.Gly411Glu and p.Arg761Gln, altered DHX9 ATPase activity. The severe NDD-associated variant p.Arg141Gln did not affect DHX9 localization but instead increased R-loop levels and double-stranded DNA breaks. Dhx9-/- mice exhibited hypoactivity in novel environments, tremor, and sensorineural hearing loss. All together, these results establish DHX9 as a critical regulator of mammalian neurodevelopment and neuronal homeostasis.

Flowthrough Capture of Microplastics through Polyphenol-Mediated Interfacial Interactions on Wood Sawdust.

Nano-/microplastics accumulate in aquatic bodies and raise increasing threats to ecosystems and human health. The limitation of existing water cleanup strategies, especially in the context of nano-/microplastics, primarily arises from their complexity (morphological, compositional, and dimensional). Here, highly efficient and bio-based flowthrough capturing materials (bioCap) are reported to remove a broad spectrum of nano-/microplastics from water: polyethylene terephthalate (anionic, irregular shape), polyethylene (net neutral, irregular shape), polystyrene (anionic and cationic, spherical shape), and other anionic and spherical shaped particles (polymethyl methacrylate, polypropylene, and polyvinyl chloride). Highly efficient bioCap systems that adsorb the ubiquitous particles released from beverage bags are demonstrated. As evidence of removal from drinking water, the in vivo biodistribution of nano-/microplastics is profiled, confirming a significant reduction of particle accumulation in main organs. The unique advantage of phenolic-mediated multi-molecular interactions is employed in sustainable, cost-effective, and facile strategies based on wood sawdust support for the removal of challenging nano-/microplastics pollutions.

Shaddock peel-derived N-doped carbon quantum dots coupled with ultrathin BiOBr square nanosheets with boosted visible light response for high-efficiency photodegradation of RhB.

In the present work, we constructed a serials of novel shaddock peel-derived N-doped carbon quantum dots (NCQDs) coupled with BiOBr composites. The result showed that the as-synthesized BiOBr (BOB) was composed of ultrathin square nanosheets and flower-like structure, and NCQDs were uniformly dispersed on the surface of BiOBr. Furthermore, the BOB@NCQDs-5 with optimal NCQDs content displayed the top-flight photodegradation efficiency with ca. 99% of removal rate within 20 min under visible light and possessed excellent recyclability and photostability after 5 cycles. The reason was attributed to relatively large BET surface area, the narrow energy gap, inhibited recombination of charge carriers and excellent photoelectrochemical performances. Meanwhile, the improved photodegradation mechanism and possible reaction pathways were also elucidated in detail. On this basis, the study opens a novel perspective to obtain a highly efficient photocatalyst for practical environment remediation.

Mitigation of exogenous melatonin on photoinhibition of tomato seedlings under chilling stress.

To understand the mitigation effects of melatonin on the chilling-induced photoinhibition in tomato, four groups of seedlings were labelled: NW (normal temperature + water), NM (normal temperature + melatonin), CW (chilling + water) and CM (chilling+ melatonin). We measured chlorophyll fluorescence, key photosynthetic parameters and the cycle efficiency for chloroplast ascorbic acid-glutathione (AsA-GSH). The results showed that, compared with the NW control, photosynthesis rate in CW was decreased by 50.3%-72.6%, chloroplast malondialdehyde content was decreased by 17.5%-132.7%, superoxide anion production was increased by 86.5%-235.9%, and H2O2 was increased by 96.6%-208.4%. These trends were significantly alleviated by exogenous melatonin, with photosynthetic rates in CM being increased by 22.7%-24.7% compared with in CW, malondialdehyde content being decreased by 16.6%-29.0%, the rate of superoxide anion production being decreased by 14.9%-22.7%, H2O2 content being decreased by 10.7%-27.1%. Compared with CW, the quantum yield of photochemical energy in PS Ⅱ was increased by 15.8% in CM, the quantum yield of regulated non-photochemical energy loss was increased by 7.2%, the quantum yield of non-regulated non-photochemical energy loss was decreased by 24.7%, and the activities of key metabolic enzymes in the AsA-GSH cycle were increased to different degrees. We concluded that exogenous melatonin application could alleviate photoinhibition in tomato seedlings under chilling by balancing the partitioning of absorption energy in PS Ⅱ and by enhancing the ROS scavenging efficiency of the AsA-GSH cycle in the chloroplast.

Peripheral-Free Calibration Method for Redundant IMUs Based on Array-Based Consumer-Grade MEMS Information Fusion.

The MEMS array-based inertial navigation module (M-IMU) reduces the measurement singularities of MEMS sensors by fusing multiple data processing to improve its navigation performance. However, there are still existing random and fixed errors in M-IMU navigation. The calibration method calibrates the fixed error parameters of M-IMU to further improve navigation accuracy. In this paper, we propose a low-cost and efficient calibration method to effectively estimate the fixed error parameters of M-IMU. Firstly, we manually rotate the M-IMU in multiple sets of different attitudes (stationary), then use the LM-calibration algorithm to optimize the cost function of the corresponding sensors in different intervals of the stationary-dynamic filter separation to obtain the fixed error parameters of MEMS, and finally, the global fixed error parameters of the M-IMU are calibrated by adaptive support fusion of the individual MEMS fixed error parameters based on the benchmark conversion. A comparison of the MEMS calibrated separately by the fusion-calibration algorithm and the LM-calibration algorithm verified that the calibrated MEMS array improved the measurement accuracy by about 10 db and reduced the dispersion of the output data by about 8 db compared to the individual MEMS in a multi-dimensional test environment, indicating the robustness and feasibility of the fusion calibration algorithm.

Metabolic control of progenitor cell propagation during Drosophila tracheal remodeling.

Adult progenitor cells in the trachea of Drosophila larvae are activated and migrate out of niches when metamorphosis induces tracheal remodeling. Here we show that in response to metabolic deficiency in decaying tracheal branches, signaling by the insulin pathway controls the progenitor cells by regulating Yorkie (Yki)-dependent proliferation and migration. Yki, a transcription coactivator that is regulated by Hippo signaling, promotes transcriptional activation of cell cycle regulators and components of the extracellular matrix in tracheal progenitor cells. These findings reveal that regulation of Yki signaling by the insulin pathway governs proliferation and migration of tracheal progenitor cells, thereby identifying the regulatory mechanism by which metabolic depression drives progenitor cell activation and cell division that underlies tracheal remodeling.

Structural engineering of BiOBr nanosheets for boosted photodegradation performance toward rhodamine B.

A series of BiOBr nanosheets were synthesized through a facile solvothermal method, whose structures were adjusted by changing solvent ratios. Their photodegradation properties toward rhodamine B (RhB) were further investigated under visible light irradiation. The photocatalytic results indicated that the B-1:3 sample showed superior photoactivity and the RhB removal efficiency attained 97% within 30 min. The outstanding photodegradation activity can be ascribed to the small particle size and thickness, suppressed e--h+ pair recombination and more active electrons and holes. Moreover, free radical quenching experiments suggest that ·O2 - and h+ play a crucial role in improving photoactivity. This work opens a new avenue to boost the removal rate of organic pollutants by engineering the solvent ratios of photocatalysts in the wastewater treatment field.

Mechanisms of Strain-Induced Interfacial Strengthening of Wet-Spun Filaments.

We investigate the mechanism of binding of dopamine-conjugated carboxymethyl cellulose (DA-CMC) with carbon nanotubes (CNTs) and the strain-induced interfacial strengthening that takes place upon wet drawing and stretching filaments produced by wet-spinning. The filaments are known for their tensile strength (as high as 972 MPa and Young modulus of 84 GPa) and electrical conductivity (241 S cm-1). The role of axial orientation in the development of interfacial interactions and structural changes, enabling shear load bearing, is studied by molecular dynamics simulation, which further reveals the elasto-plasticity of the system. We propose that the reversible torsion of vicinal molecules and DA-CMC wrapping around CNTs are the main contributions to the interfacial strengthening of the filaments. Such effects play important roles in impacting the properties of filaments, including those related to electrothermal heating and sensing. Our findings contribute to a better understanding of high aspect nanoparticle assembly and alignment to achieve high-performance filaments.

Optimizing Latent Distributions for Non-Adversarial Generative Networks.

The generator in generative adversarial networks (GANs) is driven by a discriminator to produce high-quality images through an adversarial game. At the same time, the difficulty of reaching a stable generator has been increased. This paper focuses on non-adversarial generative networks that are trained in a plain manner without adversarial loss. The given limited number of real images could be insufficient to fully represent the real data distribution. We therefore investigate a set of distributions in a Wasserstein ball centred on the distribution induced by the training data and propose to optimize the generator over this Wasserstein ball. We theoretically discuss the solvability of the newly defined objective function and develop a tractable reformulation to learn the generator. The connections and differences between the proposed non-adversarial generative networks and GANs are analyzed. Experimental results on real-world datasets demonstrate that the proposed algorithm can effectively learn image generators in a non-adversarial approach, and the generated images are of comparable quality with those from GANs.

The potential of using circulating tumour cells and their gene expression to predict docetaxel response in metastatic prostate cancer.

Background: Docetaxel improves overall survival (OS) in castration-resistant prostate cancer (PCa) (CRPC) and metastatic hormone-sensitive PCa (mHSPC). However, not all patients respond due to inherent and/or acquired resistance. There remains an unmet clinical need for a robust predictive test to stratify patients for treatment. Liquid biopsy of circulating tumour cell (CTCs) is minimally invasive, can provide real-time information of the heterogeneous tumour and therefore may be a potentially ideal docetaxel response prediction biomarker. Objective: In this study we investigate the potential of using CTCs and their gene expression to predict post-docetaxel tumour response, OS and progression free survival (PFS). Methods: Peripheral blood was sampled from 18 mCRPC and 43 mHSPC patients, pre-docetaxel treatment, for CTC investigation. CTCs were isolated using the epitope independent Parsortix® system and gene expression was determined by multiplex RT-qPCR. We evaluated CTC measurements for post-docetaxel outcome prediction using receiver operating characteristics and Kaplan Meier analysis. Results: Detection of CTCs pre-docetaxel was associated with poor patient outcome post-docetaxel treatment. Combining total-CTC number with PSA and ALP predicted lack of partial response (PR) with an AUC of 0.90, p= 0.037 in mCRPC. A significantly shorter median OS was seen in mCRPC patients with positive CTC-score (12.80 vs. 37.33 months, HR= 5.08, p= 0.0005), ≥3 total-CTCs/7.5mL (12.80 vs. 37.33 months, HR= 3.84, p= 0.0053), ≥1 epithelial-CTCs/7.5mL (14.30 vs. 37.33 months, HR= 3.89, p= 0.0041) or epithelial to mesenchymal transitioning (EMTing)-CTCs/7.5mL (11.32 vs. 32.37 months, HR= 6.73, p= 0.0001). Significantly shorter PFS was observed in patients with ≥2 epithelial-CTCs/7.5mL (7.52 vs. 18.83 months, HR= 3.93, p= 0.0058). mHSPC patients with ≥5 CTCs/7.5mL had significantly shorter median OS (24.57 vs undefined months, HR= 4.14, p= 0.0097). In mHSPC patients, expression of KLK2, KLK4, ADAMTS1, ZEB1 and SNAI1 was significantly associated with shorter OS and/or PFS. Importantly, combining CTC measurements with clinical biomarkers increased sensitivity and specificity for prediction of patient outcome. Conclusion: While it is clear that CTC numbers and gene expression were prognostic for PCa post-docetaxel treatment, and CTC subtype analysis may have additional value, their potential predictive value for docetaxel chemotherapy response needs to be further investigated in large patient cohorts.

Highly Dispersed Mo2 C Nanodots in Carbon Nanocages Derived from Mo-Based Xerogel: Efficient Electrocatalysts for Hydrogen Evolution.

The production of hydrogen via electrochemical water splitting has the potential to enable the utilization of hydrogen-powered fuel cells on a large scale. However, to realize this technology, inexpensive, noble metal-free electrocatalysts possessing high performances for the hydrogen evolution reaction (HER) are needed. Mo2 C nanoparticles recently receive much attention as alternative noble metal-free electrocatalysts because their electronic structures are akin to that of Pt. However, the synthesis of Mo2 C at nanoscale with high catalytic activity for HER remains a great challenge. Moreover, although efforts have been made to prevent their aggregation, the particles coalesce during high temperature carbonization, which is typically used to produce such transition metal carbides. Here, the synthesis of Mo2 C nanodots that are well-dispersed within 3D cage-like carbon microparticles using rationally designed Mo-based xerogels, which are prepared via the sol-gel process as precursors, is reported. During their pyrolysis, the xerogels maintain their structures while the Mo species in them transform into well-dispersed Mo2 C nanodots in situ. The as-synthesized Mo2 C nanodots exhibit excellent electrocatalytic activity for HER, in both alkaline and acidic media, while remaining largely stable. The work also demonstrates a promising synthetic route and procedure to other well-dispersed yet stable nanocatalysts.